Classifications

• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
  • G01N27/62—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating the ionisation of gases, e.g. aerosols; by investigating electric discharges, e.g. emission of cathode
  • G01N27/622—Ion mobility spectrometry
  • G01N27/624—Differential mobility spectrometry [DMS]; Field asymmetric-waveform ion mobility spectrometry [FAIMS]

Definitions

• the present invention relates generally to identification of unknown members of a sample by mobility characteristics, and more particularly to devices that analyze compounds via high field asymmetric waveform ion mobility spectrometry.
• Mass spectrometers are generally recognized as being the most accurate type of detectors for compound identification, given that they can generate a fingerprint pattern for even fragment ions.
• mass spectrometers are quite expensive, easily exceeding a cost of $100,000 or more and are physically large enough to become difficult to deploy everywhere the public might be exposed to dangerous chemicals.
• Mass spectrometers also suffer from other shortcomings such as the need to operate at relatively low pressures, resulting in complex support systems. They also need a highly trained operator to tend to and interpret the results. Accordingly, mass spectrometers are generally difficult to use outside of laboratories.
• FALMS Field Asymmetric Ion Mobility Spectrometers
• Spectrometers among other names. This type of spectrometer subjects an ionized gas sample to a varying high-low asymmetric electric field and filters ions based on their field mobility.
• the gas sample flows through a field which allows only selected ion species to pass through, according to the compensation voltage, and specifically only those ions that exhibit particular mobility responses to the field.
• An ion detector then collects detection intensity data for the detected ions.
• the intensity data exhibit attributes such as "peaks.” These peaks are interpreted according to the compensation voltage at which a species of ion is able to pass through an asymmetric field of set field parameters.
• a typical FAIMS device includes a pair of electrodes in a drift tube.
• An asymmetric field is applied to the electrodes across the ion flow path.
• the asymmetric RF field as shown in Fig. 1 A, alternates between a high or "peak" field strength and a low field strength.
• the field varies with a particular time period, t, (frequency) and duty cycle d.
• Field strength, E varies as the applied voltage V and size of the gap between electrodes. Ions will pass through the gap between the electrodes only when their net transverse displacement per period of the asymmetric field is zero; in contrast, ions that undergo a net displacement will eventually undergo collisional neutralization on one of the electrodes.
• a displaced ion can be restored to the center of the gap (i.e. compensated, with no net displacement for that ion) when a low strength DC electric field (the compensation voltage, Vcomp) is superimposed on the RF.
• Vcomp compensation voltage
• Ions with differing displacement can be passed through the gap at compensation voltages characteristic of a particular ion and this is accomplished by applying various strengths of Vcomp.
• this system can function as continuous ion filter; or a scan of Vcomp will allow complete measure of ion species in the analyzer.
• the recorded image of the spectral scan of the sample is sometimes referred to as a "mobility scan" or as an "ionogram").
• Figs. 1B-1 and 1B-2 Examples of mobility scans based on the output from a FAIMS device are shown in Figs. 1B-1 and 1B-2.
• the compounds analyzed here consisted of acetone and an isomer of xylene (o-xylene).
• Fig. 1B-1 a single compound, acetone, was independently applied to the FAIMS analyzer.
• the illustrated plot is typical of the observed response of the FAIMS device, with an intensity of detected ions dependent on the compensation voltage (Vcomp).
• Vcomp compensation voltage
• the acetone sample exhibited a peak intensity response at a compensation voltage of approximately -2 volts.
• Fig. 1B-2 illustrates the results when analyzing a mixture of the two compounds, here, acetone and o-xylene.
• the combined response shows two peaks in approximately the same region as for the independent case.
• the compounds in the mixture can therefore be detected by comparing the response against the library, for example, of stored known responses for independently analyzed compounds, or libraries of mixtures.
• the independently analyzed compounds shown in Fig. 1B-1 can be stored in a computer system, and when compound responses such as that in Fig. 1B-2 are observed, the relative locations of the peaks can be compared against the stored responses in the library to determine the constitution of the mixture.
• a problem occurs, however, especially with FALMS devices, in that relatively complex samples can be very difficult to detect.
• the peaks as seen in the typical FAIMS spectra are generally broad in width. Therefore, compounds having similar peak compensation voltages may therefore be difficult to separate from one another.
• a specific RF level and compensation voltage will permit only a particular species of ion (according to mobility) to pass through the filter to the detector.
• various ion species can be identified, as well as their relative concentrations (as seen in the peak characteristics).
• This coefficient of mobility is considered to be a unique parameter that enables the identification of different ion species and is determined by, ion properties such as charge, size, and mass as well as the collision frequency and energy obtained by ions between collisions.
• K is constant in value, but at increasing E/N values, the coefficient of mobility begins to vary.
• the effect of the electric field can be expressed approximately as
• K(E) K(0)[l+ ⁇ (E)] where K(0) is a low voltage coefficient of mobility, and a is a specific parameter showing the electric field dependence of mobility for a specific ion.
• Fig. IB demonstrates that each species can have a unique behavior in high fields according to its mobility characteristics.
• the ions passing through the filter are detected downstream.
• the detection signal intensity can be plotted, resulting in display of a characteristic detection peak for a given RF and Vcomp. Peak intensity, location, and shape are typically used for species identification.
• a problem occurs, especially with FAIMS devices, in that relatively complex samples can be very difficult to discriminate.
• the peaks as seen in the typical FALMS spectra are generally broad in width. Therefore, compounds having similar peak compensation voltages may be difficult to separate from one another. Indeed, there may be particular conditions where two different chemicals actually exhibit the same peak at the same compensation voltage at a given asymmetric RF field.
• Fig. ID there are four compounds each with a unique characteristic mobility curve that expresses the mobility dependence associated with that compound at each of various peak RF values and compensation voltage levels.
• Four different chemical compounds are shown, including lutidine, cyclohexane, benzene, and a chemical agent simulant dimethyl-methyl- phosphonate (DMMP).
• DMMP dimethyl-methyl- phosphonate
• Each curve shows detection peaks at the various field conditions that in total are characteristic for the compound.
• a cylindrical FALMS device is described in US patent number 5,420,424, where the amplitude of the asymmetric periodic potential is in the range of about 1 to 6 Kv or 2 to 5 Kv, and preferably at about 3 Kv, depending on the ionic species of interest.
• the compensation voltage is held constant or scanned to provide separation of the ionic species.
• the present invention is directed to a method and system for identification of unknown species of ions traveling through an asymmetric excitation field, the identification being based on the known characteristic mobility behavior of ion species under known field conditions.
• Illustrative apparatus of the invention includes an ionization section, a filter section, a detection section, an identification section, and a controller section.
• the controller e.g., microprocessor, laptop, etc.
• the controller may typically incorporate the identification section (lookup table, comparator, etc.).
• This process may also include separating the ions from background noise or from other ion species in the sample.
• the present invention intentionally controls and uses changes of the filter field (i.e., changes in "field conditions") for better revealing and isolating ion species in the sample.
• the ionization and filter sections may assume many different physical forms.
• Vcomp compensation voltage
• Vrf set RF condition
• the present invention then takes this process further.
• stratagem for improving species discrimination by intentionally controlling field conditions in a manner that results in improved isolation of ion species involves detecting ion species behavior in response to at least two different applied RF field strengths, and thus at two different sets of field conditions.
• At each ion species detection we associate the applied compensation and RF with the detection signal and match or correlate this with known data to identify the detected ion species.
• adjusting field conditions including adjusting field strength, frequency, aspects of the waveform asymmetry, pulse shape, duty cycle, and the like, to effect meaningful changes in field conditions that affect ion mobility.
• These alternatives are selected for the ability they provide in separating and isolating ion species in the sample. This assumes that the ion species are sensitive to such changes.
• this control In all events these controls are directed to causing one species to behave differently from another species in the field so, that a more refined or better defined set of ions can be passed to the detector.
• field conditions and “set of field conditions” as any combination of compensation and RF established in the gap between the filter electrodes as may affect ion mobility.
• Field conditions are considered to be different when attributes of the RF or compensation have been changed, whether this takes the form of adjustment in frequency, intensity, asymmetry, periodicity, pulse shape or similar variables. Nevertheless, we can control the field conditions and the energy in the field in a manner that has differential effect upon ion mobility in the field. We use this differential effect in controlling ion filtering.
• field conditions also will be understood to take into account various other aspects such as temperature, flow rate, pressure, and flow volume in the filter, as well as the nature of the carrier gas, if any.
• Field conditions can be controlled by several techniques in practice of the invention. For example, frequency has an effect on the 'selectivity' (width) of the output scanned peaks. This can be implemented by changing the value of a fixed operating frequency or by dynamic frequency modulation where a range of frequencies could be scanned, for example. Control of pulse shape, i.e., square, triangular, sinusoidal, ramp, also may be adjusted, where shape may be used to affect response of the ion in the field in a known manner. Magnetic fields may also be used to control flow of ions according to known response characteristics.
• the compensation voltage Vcomp may be a separate DC voltage or it may be imposed on the RF signal Vrf, such as by varying the duty cycle.
• the term compensation therefore will be understood as an adjustment to the field by bias voltage or other means that enables tuning the field to pass a desired species of ion to the detector.
• varying the duty cycle or pulse width can have an effect similar to adjusting or scanning the compensation voltage. The latter can be accomplished by holding the pulse width constant while varying the frequency or by holding the frequency constant while varying the pulse width.
• compensation can be generated by varying baseline voltage.
• These controls can be produced with analog circuitry or can be generated digitally.
• These and still other control strategies are within the spirit and scope of the invention as will appear to a person skilled in the art. We therefore exercise our ability to control ion behavior in the electric field by. control of field conditions, knowing that different ion species will pass through the filter depending upon these field conditions. In one example, we set the field strength, e.g., amplitude of the RF signal, and then adjust or shift the compensation to a level needed to detect an ion species.
• a "reactant ion peak” may be detected in a FAIMS device and will be associated with ions that result from ionization of the background environment in the drift tube.
• This background may include molecules of carrier gas that are ionized, and perhaps also water molecules that become protonated, during the ionization process. Peaks associated with detection of these ions are referred to as “reactant ion peaks” as opposed to peaks associated with detection of chemical ions of interest.
• increasing the RF field strength typically has a much more dramatic effect on the background RIP than on a sample ion species; as a result of sampling at two or more of a series of different field conditions (whether the difference' is in the RF field or the compensation), the RTP peak can be shifted away from the peak for an ion species of interest.
• This separation of detection data isolates the ion species of interest from the background detection data and results in a cleaner and more accurate species detection and identification. In this manner, detection accuracy is improved and false positives are reduced in practice of the invention.
• a single complex compound may be identified by its characteristic component ions or sub-clusters, again based on comparison of field conditions and detection data compared to a known data store.
• we control ionization such as by increasing ionization energy and fragmenting the sample into characteristic component parts. This increases specificity of the detection data.
• detection intensity data This characterizes an ion species detection of unknown type.
• This detection data is compared to stored detector data for known species at known filed conditions and a detection identification is made. This approach is simplified, but may be adequate for various embodiments of the invention.
• a detection is made of an ion species at at least two field conditions. Identification is made by collecting multiple detection data representing a signature of the detected ion species in these field conditions, and then by comparing this signature data to a store of known species signatures.
• the ion species to be identified may be traveling alone or in a group of ions of same or differing characteristic mobility behavior.
• a FAIMS device operates simultaneously in both positive ion detection mode ("positive mode” or “positive ion mode”) and negative ion detection mode ("negative mode” or “negative ion mode”) for -Incomplete real-time sample analysis.
• two separate FALMS devices may operate in tandem, one in each mode, and detection results can be processed either seriatim or simultaneously and combined for complete realtime sample analysis.
• a preferred method and apparatus detects multiple species simultaneously based on both ion mobility and ion polarity.
• a preferred method and apparatus of the invention includes a planar FALMS spectrometer applied to filtering and simultaneous transport and detection of positive and negative ion species from a sample including mercaptans and other sulfur-containing compounds, and air, methane or other gases.
• a compensated asymmetric high RF field is used to separate sulfur-containing compounds (such as mercaptans) from a hydrocarbon background (such as methane).
• the sample is ionized and the ions representing sulfur-containing compounds (such as mercaptans) are detected according to polarity (i.e., for the most part as negative ions).
• the hydrocarbons are detected according to polarity (i.e., for the most part as positive ions) in the same device.
• the invention enables detection of trace amounts (ppm, ppb, ppt) of mercaptan in varying and even high hydrocarbon backgrounds.
• the device is also able to characterize the hydrocarbon gas backgrounds.
• a preferred practice of the invention has the ability to detect trace amounts of sulfur-containing compounds (e.g., mercaptans) in varying and even high hydrocarbon backgrounds and to characterized the hydrocarbon backgrounds in the same device simultaneously.
• a gas sample having sulfur- containing compounds e.g., mercaptans
• methane or other gases including air
• Negative ions are detected indicative of the concentration and identity of the sulfur-containing compounds.
• the same test is run again and positive ions are detected indicative of the hydrocarbon gas in the sample.
• These compounds are passed by the FALMS filter based on their mobility behavior and their having similar trajectories in the presence of compensated electric filter fields.
• the passed ions are then further separated based on polarity, wherein, for example, mercaptans can be distinguished from a gas such as air or methane.
• mercaptans In the negative mode, mercaptans are detected and in the positive mode, the gas (e.g., methane) is distinguished from the mercaptans. Both modes can be run simultaneously.
• samples such as hydrocarbon gas will separate into predominantly positive ion species and sulfur-containing compounds (e.g., mercaptans) will separate into predominantly negative ion species.
• the preferred planar FALMS spectrometer is a simple and low cost device, which can perform substantive quantitative analysis of complex mixtures having sulfur-containing compounds (e.g., mercaptans) in a gas, such as hydrocarbon or air.
• a single positively biased detector electrode downstream from the filter will detect the negatively charged ion stream (negative mode).
• a single negatively biased detector electrode downstream from the filter will detect the positively charged ion stream (positive mode).
• a detection signal is generated as these ions deposit their charges on a detector electrode. These detections can be correlated with the RF signal, compensation voltage and detector bias, to identify the detected ion species.
• both positive and negatively charged ion species can be detected and identified.
• the asymmetric voltage applied to the ion filter electrodes ranged from about 900 to about 1.5 kV (high field condition), and a low voltage of about -400 to -500 V (low field condition).
• the frequency ranged 1-2 MHz and the high frequency had an approximate 30% duty cycle, although other operating ranges are possible.
• the detector electrodes were biased at +5v and -5v. Now the mercaptans are detected in the negative mode and the hydrocarbon gases can be detected in the positive mode.
• the field-dependent mobility of a species can be expressed as an function.
• the coefficient of field-dependent mobility, ⁇ , for a species is expressed as a function of the electric field.
• the resulting curve showing the experienced mobility or "of' curve, is a unique signature for that species.
• this signature can be expressed in a device-independent function.
• the characteristic mobility for each species can be plotted at multiple field conditions (i.e., detection intensity noted at a series of field conditions), and this and can be expressed as a unique " ⁇ function" that identifies the ion species uniquely.
• this mobility curve is species specific, and we have further identified a process for making such identification device-independent. In any case, we compare detected and computed data to a store of known data to make positive identification of the species of detected ions.
• the system of the present invention (which may be expressed as either method and/or apparatus) is for identification of species of unknown ions that travel through a varying excitation field.
• the field is characterized as having varying influence upon the mobility behavior of the species (single or plural) of ions (single or plural) traveling through the field.
• the identification of the detected ion(s) is based on correlating the field-dependent mobility behavior of the detected ion(s) to a store of known field-dependent mobility behavior(s) of at least one known species.
• Fig. 1 A illustrates an asymmetric field having a peak RF, time period, and duty cycle.
• Figs. 1B-1 and 1B-2 are a typical display of detected abundance versus applied compensation voltage for a given field strength in a field asymmetric ion mobility spectrometer, first for acetone alone and second for a combination of o-xylene and acetone (Prior Art).
• Fig. 1C is a plot of mobility dependence upon electric field strength for three different compounds (Prior Art).
• Fig. ID is a plot showing peak detections across a range of combinations of peak Radio Frequency (RF) voltage and compensation voltage for four different compounds (Prior Art).
• RF Radio Frequency
• Fig. 2 is a schematic of a preferred planar field asymmetric ion mobility spectrometer in practice of the present invention.
• Figs. 3A and 3B illustrate positive and negative mode spectra for different amounts of ethyl mercaptan in practice of the present invention.
• Figs. 3C through 3G illustrate the affect of changes in field conditions, such as changes in compensation, on specific spectra, and showing divergent behavior of monomer and reactant ion peak (RTP) detections with changes in field for detecting sulfur hexafluoride (SF6) in practice of the invention.
• RTP monomer and reactant ion peak
• Figs. 4A and 4B illustrate changes in peak location change in compensation in practice of the present invention.
• Figs. 5 A and 5B illustrate ability to discriminate between detected ion species by changes in field conditions in practice of the present invention.
• Figs. 6 A and 6B illustrate the affect of changes in field conditions, such as changes in compensation, on specific spectra, and showing divergent behavior of monomer, cluster, and reactant ion peak (RIP) detections with changes in field for hexanone and octanone in practice of the present invention.
• Fig. 7 illustrates effect of changes in field conditions on location of individual detection peaks and ability to separate peaks in practice of the present invention.
• Figs. 8A and 8B respectively show a plot of compensation versus field strength for detected monomer and cluster ion peaks for a family of ketones in practice of the present invention.
• Fig. 8C includes Table 1, which is a collection of detection data from which the curves of Fig. 8 A and 8B were generated for a group of monomer and dimers (clusters) for eight ketones in practice of the present invention.
• Figs. 9 A and 9B illustrate the results of calculating normalized alpha parameter curves in practice of the present invention.
• Fig. 10A shows a sequence of steps of a computer process used to acquire data concerning a particular chemical ion species in practice of the present invention.
• Fig. 10B shows a diagram of one possible data structure for a library of stored compound data measurement information in practice of the present invention.
• Fig. 10C is a series of steps that may be applied to perform a chemical recognition in practice of the present invention.
• Fig. 10D is a series of steps that may be added to the data acquisition and chemical recognition processes using alpha curve fitting in practice of the present invention.
• Fig. 10E is a diagram of a more complex data structure that can be used in practice of the present invention.
• Fig. 1 OF is a sequence of processes that may be used to distinguish monomer and cluster peak responses in practice of the present invention.
• Fig. 10G is a diagram of a process showing how monomer and cluster scores maybe combined in practice of the present invention.
• the present invention has particular application to high field ion mobility spectrometry and includes the recognition that improved identification or discrimination of compounds may be achieved.
• the invention may be practiced in many different field-driven and gas-driven embodiments.
• One aspect of our innovation can be stated in terms of the steps of a process. Specifically, a system is used to cause species of unknown ions to travel through an excitation field. The field has a varying influence upon the behavior of different ions as they travel through the field. Identification is based on this known field-dependent behavior of different species of ions. Identification of the species may occur by comparison of results observed under one set of field conditions with results observed under another set of field conditions.
• a planar Field Asymmetric Ion Mobility Spectrometer (FALMS) apparatus 10 The apparatus has a sample flow section 10 that accommodates the flow of a carrier gas G which carries sample S from sample inlet 12 at one end of the flow channel 11 to a sample outlet 13 at the other end of the flow channel.
• FALMS Field Asymmetric Ion Mobility Spectrometer
• the sample is drawn from the environment or received from a front end device, such as a gas chromatograph, and flows into an ionization region 14.
• Compounds in the sample are ionized by an ionization source 16 as the sample flows through the ionization region 14, creating a set of ionized molecules 17+, 17-, with some neutral molecules 17n, of various chemical species that are in the sample S.
• This may include monomer ions and cluster ions. Such clusters may be created when a monomer combines with water molecules or other background molecules, and the combination is ionized.
• the carrier gas carries the ionized sample into the ion filter region 18 in between filter electrodes 20, 22 of ion filter 24.
• Filtering proceeds now based on differences in ion mobility in the filter field, which is influenced by ion size, shape, mass and charge. More specifically, an asymmetric field applied across the filter electrodes alternates between high and low field strength conditions in filter region 18.
• the ions move in response to the field, based on their mobility characteristics. Typically the mobility in the high field condition differs from that of the low field condition. This mobility difference produces a net transverse displacement of the ions as they travel longitudinally through the filter 24, defining an ion trajectory.
• the carrier gas (or other flow mechanism) carries the ionized sample into the ion filter region between the filter electrodes. Filtering proceeds based upon differences in ion mobility, which is influenced by the ion size, shape, mass, and charge. This enables discrimination of ions species based upon their mobility characteristics.
• an asymmetric field voltage or dispersion voltage is applied across the filter electrodes as an RF voltage driven between high and low field strength conditions.
• This excursion causes the ions to move transverse to the flow as they flow through the flow channel, with the transverse motion being representative of their characteristic ion mobility.
• the mobility in the high field condition differs from that of the low field condition. This mobility difference produces a net transverse displacement of the ions as they travel longitudinally through the filter between the electrodes.
• the compensation voltage, Vcomp causes a particular ion species to be returned toward the center of the flow path, thus being able to exit the filter without colliding with the filter electrodes and without being neutralized. Other species will not be sufficiently compensated and will collide with the filter electrodes 20, 22 and will be neutralized.
• the neutralized ions are purged by the carrier gas, or by heating the flow path 11, for example.
• the device of Fig. 2 can be operated to simultaneously detect both positive and negative ions in the gas flow, enabling identification of two compounds simultaneously or enabling detection of two modes of a single compound simultaneously. More specifically, the two species of ions 17+ and 17-, enter the detection region 25 where further separation occurs followed by their intensity determination.
• the detector 26 includes a first detector electrode 28 and a second detector electrode 30. Electrode 28 may be positively biased and therefore attracts ion 17- and repels ion 17+. Electrode 30 may be biased negatively, and attracts ions 17+ while repelling ions 17-.
• this final stage of separation terminates with the separated ions depositing their charges on the appropriately biased detector electrodes 28 or 30.
• the signals generated by the ions collecting at detector electrodes 28 and 30 are amplified by respective amplifiers 36 and 38 to provide signals to command and control unit 34.
• the invention applies to high field asymmetric waveform ion mobility spectrometry in a planar device configuration such that the flow channel 18, filter electrodes 24, and detector electrodes 28 are all provided in a planar package.
• This provides for the ability to produce a compact, low cost device which may have incorporated upon a common substrate the various system components and possibly support electronics.
• Spectrometers according to the present invention may therefore be manufactured using well known microchip manufacturing techniques while at the same time providing highly effective analytical equipment for use both in the field and in laboratory environments.
• ions having specific mobility characteristics will be returned toward the center of the flow path and will pass through the filter. Therefore, in practice of the invention, discrimination of ions from each other according to the compensation results in a ions having a particular mobility passing to detector 26 (which may be an on-board electrode arrangement or may include an off-board detector such as a mass spectrometer, for example). All other species will not be sufficiently compensated and will collide with the filter electrodes and will be neutralized.
• the invention applies to high field asymmetric waveform ion mobility spectrometry in a planar device configuration such that the flow channel 18, filter electrodes 24, and detector electrodes 28 are all provided in a planar package.
• This provides for the ability to produce a compact, low cost device which may have incorporated upon a common substrate the various system components and possibly control electronics 40.
• Spectrometers according to the present invention may therefore be manufactured using well known microchip manufacturing techniques while at the same time providing a highly effective analytical equipment for use both in the field and in laboratory environments.
• the control unit 40 contains a number of electronic devices that perform a number of important functions in accordance with the present invention. These include RF voltage generator 42, compensation voltage generator 44, a microprocessor unit (MPU) 46, memory 47, an analog-to-digital converter 48, and display 49.
• the microprocessor 46 provides digital control signals to the RF (AKA "dispersion") voltage generator 42 and compensation voltage generator 44 to generate the desired drive voltages for the filter 24, respectively. They may include, for example, digital-to-analog converters that are not shown in detail.
• the microprocessor 46 also coordinates the application of specific dispersion voltages Vrf and compensation voltages Vcomp with observed responses from the detector 26, as read through the analog-to-digital converters 48.
• the microprocessor 46 can identify particular compounds such as by comparing particular response curves against a library of response curves or other data stored in its memory 47. The results of the comparison operation can then be provided in a form of an appropriate output device such as a display 49, or may be provided by electrical signals through an interface 50 to other computer equipment.
• a range of applied peak RF voltages may run from less than 1,000 V/cm to 30,000 V/cm, or higher.
• the frequency ranges may run from 1 to 20 Megahertz (MHz), with the highest frequencies having an approximately 30 percent duty cycle, although other operating ranges, voltages, field strengths, duty cycles, wavelengths and frequencies are possible in embodiments of the present invention.
• the processor 46 scans or sweeps a range of compensation voltages (i.e., a scan) for a particular RF field strength as controlled by the applied peak RF (dispersion) voltage for a first measurement set, and then the RF is reset to another level and the compensation voltage is scanned again to establish a second measurement set.
• This information is correlated with detection signals obtained as set forth above, and compared to look up tables, a compound identification is able to be made. More generally stated, an object of identification is to detect the intensity of the ions passing though the filter and to associate this intensity with field conditions.
• Each identified compound is to be associated with at least one particular spectral peak and then we can use the process of peak evaluation or peak matching to identify compounds, peak by peak. This process is not limited to single peaks and multiple peaks detected in a single scan also can be used to define a signature for the responsible particular combination of compounds. If it is a recurring phenomenon, then such complex signature can be part of our table of look up data.
• a particular combination of peaks in a spectral scan is known and important, data representing these multiple peaks can be stored and future detection data can be compared against this stored data. For example, under controls field conditions, such as at raised field strengths, a clustered compound may become declustered. The resulting detection results in a signature of peaks that can be used to identify the source compound being detected even in as detected in a single scan.
• an ion mobility-based method and apparatus for detection of sulfur-containing compounds in a hydrocarbon background In one example, detection and measurement of negative ions is done in a negative mode, and detection and measurement of positive ions is done in a positive mode. The detected data enables a quantitative measurement of concentration of these sulfur-containing compounds, independent of the hydrocarbon background.
• a single positively biased detector electrode 30 (or 28) downstream from the filter can be used to detect the negatively charged ion stream (negative mode), and optionally another other electrode 28 (or 30) may be negatively biased to deflect the negative ions to the positively biased detector electrode.
• a single negatively biased detector electrode 28 (or 30) downstream from the filter can also detect the positively charged ion stream (positive mode), and optionally the other electrode 30 (or 28) may be positively biased to deflect the positive ions to the negatively biased detector electrode.
• positive and negative modes may be detected in the FAIMS spectrometer, seriatim or in parallel devices.
• a single positively biased electrode 30 downstream from the filter is used to detect the negatively charged ion stream (negative mode); meanwhile electrode 28 is negatively biased to deflect the negative ions to this positively biased detector electrode 30 so as to improve collection efficiency.
• the negatively biased electrode 28 detects the positively charged ion stream (positive mode) that is deflected by the positively charged electrode 30.
• a detection signal is generated as these ions deposit their charges on a respective detector electrode. These detections can be correlated with the RF signal, compensation voltage and detector bias, to definitively identify the detected ion species. Thus Where two detector electrodes are provided downstream, each oppositely biased, both positive and negatively charged ion species can be detected and identified simultaneously.
• the present invention was used for detection of trace amounts (ppm, ppb, ppt) of mercaptan in varying and even high hydrocarbon backgrounds.
• the device is also able to characterize hydrocarbon gas backgrounds.
• the present invention is capable of detecting mercaptans, such as ethyl mercaptan in a methane background, and is also capable of detecting a gas, such as methane, in a mercaptan background.
• the asymmetric voltage applied to the ion filter electrodes ranged from about 900 to about 1.5 kV (high field condition), and a low voltage of about -400 to -500 V (low field condition).
• the detector electrodes were biased at +5v and -5v. Now the mercaptans are detected in the negative mode and the hydrocarbon gases can be detected in the positive mode.
• the hardware used to drive the system my be conventional.
• amplifiers such as Analog Devices model 459 amplifier
• the signal may be processed in a conventional manner, such as with a National Instruments board (model 6024E) to digitize and store the scans and with software to display the results as spectra, topographic plots or graphs of ion intensity versus time.
• the ionization source may be a plasma or radioactive source or a UV lamp, or the like.
• the present invention recognizes that ions that pass through the filter define a mobility species 17m. In a further example, this species can be further separated by polarity, such as by correct biasing of the detector electrode pair 28, 30. An example is shown in Fig.
• ions 17+, 17- passes through filter 24.
• This species can be further separated to positive and negative species or sub-species by holding one electrode, e.g., detector electrode 28, at one polarity, say negative, and another electrode, e.g., detector electrode 30, at a positive bias. Now ions 17+ will be attracted to electrode 28 and will be detected and ions 17- will be attracted to and will be detected at electrode 30.
• apparatus of the invention can be operated to simultaneously detect both positive and negative ions in a species flowed from the filter. This enables identification of multiple compounds simultaneously in practice of the innovation. More specifically, the apparatus 10 discriminates between ions and neutrals based on their mobility behavior, resultant trajectory and polarity. Therefore only ion species 17- and 17+ with a particular mobility behavior and resultant trajectory in the presence of a given compensation bias will be passed by the filter, for a given asymmetric RF field condition. It will be appreciated by a person skilled in the art that this compensation bias must be established for the compounds being tested.
• the apparatus of the invention is very stable and test results are repeatable.
• creation of a history table for species of ions detected, correlated with compensation voltage and RF field enables continuous use of the device without the need for further calibration.
• a mobility species 17m was passed by filter 24. That species included hydrogen sulfide ions 17m- and methane ions 17m+, both of which have a similar resultant trajectory, for given compensated asymmetric field. Other positive and negative ions are neutralized given their different and unselected mobility characteristics. (Neutralized ions 17n are purged by the carrier gas or by heating the flow path 11, for example.) The two species of ions 17m+ and 17m- have entered into the detection region 25, where further species separation occurs, followed by detection. In a preferred embodiment, detector electrode 28 is biased positive and therefore attracts hydrogen sulfide species 17m- while repelling methane species 17m+.
• Electrode 30 is biased negative and attracts methane species 17m+, while deflecting sulfide ions 17m-. Thus this final stage of separation results in the separated ions depositing their charges on the appropriately biased detector electrodes (i.e., negative charge on positive electrode and positive charge on negative electrode).
• the asymmetric field and compensation bias are generally applied to filter electrodes 20, 22 by drive circuits 32 within command and control unit 34.
• the signals generated by the ions at the detector electrodes 28, 30 are amplified by amplifiers 36, 38, also under direction and control of unit 34 (communicating by wires, ribbon cable, or the like).
• a computer (or microprocessor) including a data store, generally shown at 40 correlates historical data for the device with the drive signals applied to the filter electrodes and with detection signals from amplifiers 36, 38, and presents a compound identification information to a readout device 49. In this example, an indication of the amount of hydrogen sulfide and of methane detected would be indicated.
• the command and control unit 34 also coordinates ion flow and the application of specific dispersion voltages Vrf and compensation voltages Vcomp with observed responses from the detector 26.
• the microprocessor can identify particular compounds such as by comparing particular response curves against a library of response curves stored in its memory. The results of the comparison operation can then be provided in a form of an appropriate output device such as at a display, or may be provided by electrical signals through an interface to other computer equipment.
• a single spectrometer device 10 provides a detector with dual detector electrodes 28, 30. One electrode may be positively biased and the other negatively.
• the negatively biased detector electrode acts for ions of the same polarity as a deflector electrode, deflecting those ions toward the positively charged detector electrode for detection.
• the one detector electrode that is positively biased acts for ions of the same polarity as a deflector electrode, deflecting those ions toward the negatively charged detector electrode for detection.
• each of these detector electrodes has a dual role, acting as both a deflector electrode and detector electrode, for respectively charged ions.
• the compensation bias is in the form of varying the duty cycle of the asymmetric field, without the need for compensating bias voltage. In any such manner, the apparatus is tunable, i.e., it can be tuned to pass only desired selected mobility species, which can be further clarified with the above polarity mode detections.
• the high voltage RF signal is applied to one filter electrode, e.g., electrode 20, and the other electrode, e.g., electrode 22, is tied to ground.
• a compensation voltage is then applied to one or across the filter electrodes according to the ions species to be passed.
• Figs. 3 A and 3B we show detection of ethyl mercaptan independent of varying background gas level.
• Fig. 3 A shows positive ion detection mode ("positive mode") detection, where a detector electrode is negatively biased and attracts positive methane ions 17m+ for detection.
• Fig. 3B shows the effect of varying methane concentration on ethyl mercaptan spectra in the negative ion mode ("negative mode").
• negative mode a detector electrode is positively biased and attracts the negative mercaptan ions 17m- for detection.
• a mercaptan sample when ionized may have predominantly negative ions, but may also include positive ions.
• Now identification can be more accurate and false positives reduced by using both modes simultaneously to state a unique detection signature.
• the negative mode fairly identifies the mercaptan
• the added positive ion identifier related to mercaptan enables identification in a complex sample.
• the stored lookup data of known device performance and known species signatures may be accessed for either single mode or simultaneous mode detections. By comparison with historical detection data for the device, these peaks can be clearly identified as the tell-tale spectra of the mercaptan. Both spectra give clear indication of the mercaptan, qualitatively and quantitatively. Running both modes simultaneously clearly identifies the sample with unique and definitive detection data which can be compared to and matched with stored data to identify the detected ions.
• the present invention is capable of realtime analysis of a complex sample, such as one containing mercaptans and hydrocarbon gas, because these ions are relatively of the same mobility and can pass through the filter under the same field conditions.
• Simultaneous positive and negative mode detection in a single mobility scan thus provides a richness of detection data.
• This increased identification data results in a higher level of confidence, and reduced false positives, in compound identification. This is a valuable improvement over the simple prior art FALMS method of peak identification.
• the data that can be obtained from a negative mode scan is normally different from that of a positive mode scan. While identification of a compound may be achieved by using one mode only, the used of detections from both modes makes for a more definitive identification with lower likelihood of error.
• ions are identified based on not a single set of field conditions, but based on multiple intensity data detected at at least two and possibly additional numbers of high field conditions (i.e., at at least two field measurement points). Detections are correlated with the applied RF voltage and compensation, at the at least two different field conditions, to characterize a given detected compound. Because multiple detection data are associated with a given ion species of interest, more accurate detections can be made. Comparison with stored data results in reliable identification of detected compounds.
• This family of points can then be plotted to determine the mobility curve signature for specific species as a function of RF peak voltage and compensation.
• field condition data e.g., field strength and compensation voltage for two nearby detections of the same ion species.
• the selection of measurement points and the number of measurement points may be adjusted for the specificity required for a particular application.
• the minimum number of measurement points is two, which at least identifies an aspect (such as slope) of the characteristic curve for a compound, given the known field values.
• each compound has a unique characteristic mobility curve that expresses the peak detection data associated with that compound at each of various associated peak RF and compensation values.
• detection of four different chemical compounds is shown including lutidine, cyclohexane, benzene, and a chemical agent simulant dimethyl-methyl-phosphonate (DMMP).
• DMMP dimethyl-methyl-phosphonate
• Each curve shows detection peaks at the various field conditions that is characteristic for the compound.
• the plot of compensation voltage versus dispersion voltage (i.e., RF peak voltage) in Fig. 1C shows the associated compensation voltage for the spectral peak for each of the particular compounds illustrated at a given RF peak.
• a preferred practice of the present invention contemplates stepping the RF peak voltages and scanning the compensation voltages to generate unique sets of data that identify and distinguish the detected compounds to create a data store of mobility signatures. We then have a data to store for lookup that characterizes these mobility curves and can be used for compound identification. This process will be explained in greater detail in connection with Figs. 10A-10F.
• FIGs. 4 A and 4B showing detection intensity (abundance) as a function of compensation voltage at a particular applied field strength.
• Fig. 4 A peaks 110-1, 110-2, 110-3, and 110- 4 occur at a given Vcomp, with Vrf at 1400v (with a field strength of 28,000v/cm).
• Vrf field strength of 29,000 v/cm
• a match to stored data for both field conditions for these isomers would provide a reliable ion species identification with low likelihood of false positives.
• a hand-held device that merely looks at these two or similar "data points" would be delivered in practice of the invention as a handy xylene detector.
• Figs. 6A and 6B we show the effect of changes in field strength on the location of detection peaks at different compensation levels for hexanone and octanone.
• FIGs. 6A and 6B present a series of plots of the response of a FAIMS device with different applied field strengths. The curves are offset on the vertical axis, with the offset increasing as electric field strength increases. While various operating ranges are possible, as an illustration, Figs. 6 A and 6B may be understood as presenting the peak RF between a low of around 620 volts (lowermost plot in each) and a high of around 1450 volts (uppermost plot in each).
• RIP 605-m decreases markedly with the increase in the electric field.
• RIP 605-m is observed at much lower amplitude and well separated from the monomer peak 601-m of interest at a specific field condition. While the monomer peaks 601 also shift, they do not shift by the same amount, or even as much.
• a condition can be discovered at which the RIP 605 will shift away from, or perhaps even shift off the scale of, other observed peak voltages. In some cases this allows easier detection of the monomer ion peak 601 of interest.
• the cluster ions 608 represent clusters of chemical materials in the sample.
• Typical cluster ions having a heavier chemical weight, have peaks that are shifted differently from monomer ion peaks of interest. In particular, given that they are heavier, the cluster peaks shift differently. In this example, the cluster peaks shift in a direction away from the direction of shift of the monomer peaks with increasing applied field strength.
• This characteristic feature of cluster ions observed with this sample can also be stored and utilized in recognizing the hexanone or octonone ions.
• 6A and 6B are but one example of how applying a range of field conditions to detect a given sample can be utilized to advantage. Another effect can be observed with the application of relatively high field strengths. Specifically, complex ion groupings can be fragmented with higher field strength so that the components of the group themselves can be individually detected.
• SF6 Sulfur hexafluoride
• the response in the positive mode while alone not definitive, has a profile and thus in combination with the negative mode is confirmative and provides a lower likelihood of false detections.
• SF6 gas is used in atmospheric tracer applications to monitor air flow, as a tracer for leak detection in pipes to point detect sources of leaks, in power plants to isolate switches to reduce, or prevent breakdown of the switches, among other uses. Isolation and detection of SF6 is often found to be a difficult proposition.
• the reactant ion peak is composed of the ionized nitrogen and water molecules in the air.
• IMS time of flight
• Fig. 3E there is a plot of the FALMS response at different RF voltage levels in the negative ion mode.
• Fig. 3F shows this result and also shows the RTP detected in absence of SF6.
• the FALMS filter of the invention with appropriate selection of RF and compensation voltages is shown.
• the SF6 peak is shifted from and distinct from the RIP.
• Fig. 3G shows that FAIMS response in the positive ion mode (detecting positive ions passing through the FALMS ion filter), where the SF6 peak is not isolated from the RTP. While alone this is not definitive, it is an expected detection and therefore may be used as confirmative when combined with a definitive SF6 negative mode detection.
• a portable battery powered unit for the detection of SF6 with a sensitivity of 1x10-9 atm cc/sec SF6 (0.01 PPM) is enabled.
• the invention may be used, for example, in the power industry to ensure the leak tightness of High Voltage Switchgear and in the laboratory for testing fume hoods to the ASHREA 110 specification.
• Fig. 7 is an example of such an affect on a mercaptan ion sample.
• a range of background voltages (from 620 - 1450 volts) were applied to an ethyl mercaptan spectra in which we see a general shift of ion peak behavior as an electric field conditions are strengthened.
• a fragmentation condition Specifically, at lower applied field conditions, strong single peak is observed, such as at 701-1.
• FIGs. 8A and 8B we have plotted experimental detection data recorded in Table 1 (Fig. 8C) for a homologous group of ketones, including: acetone, butanone, pentanone, hexanone, heptanone, octanone, nonanone, decanone (8A- monomers, 8B- clusters).
• Each species has a unique mobility curve, and thus a unique mobility signature, for the given set of field conditions.
• a match enables identification of the detected ketone in that device.
• curve data such as slope and sign
• E peak RF field strengths
• the multiple data represented in Figs. 4A and 4B and 5 A and 5B each can be used to provide positive identification of a detected species by the unique and inherent mobility characteristic that identifies that species.
• a lookup table that can be specific to the device in question, but also can be a universal set of data that is device- independent.
• Alpha coefficient determination More specifically, in computing mobility signatures, we have found that an expression of the field-dependence of ion mobility, the so-called coefficient, expressed as a function of field, can be used to generate a unique function that is inherent for that species and is device independent. Thus the a function can be used as the unique signature of a species; quite remarkably, this function expresses both a characteristic signature for the ion species and is device independent. In short, we recognize that peaks change position in signature ways because they have different alpha signatures.
• a function as a mobility signature for detected species.
• the signature can be determined for a detected unknown compound based on the field conditions that are used, and then this can be used to make an identification according to a lookup table of stored known signature data associated with known compounds. More particularly, in practice of a preferred embodiment of the invention, ion species are identified based on the mobility dependence of the species under various field conditions. Data is collected for the sample under test for at least two field conditions, the data is processed, and a comparison of detection data computed as an function for the sample under test versus the stored data enables identification of the compounds in the sample. Referring again to the discussion of the parameter, Fig.
• IB is a plot of mobility versus electric field strength for three examples of ions, with field dependent mobility (expressed as the coefficient of high field mobility, shown for species at greater, equal to and less than zero. For any given set of field conditions, the field strength and compensation can be correlated with an value. This is shown in the work of Buryakov et. al., A New Method Of
• ⁇ (E) an ion's mobility characteristic as a function of field
• ⁇ (E) or "alpha function” relates the size, effective cross-section, shape, and mass of the ion to field conditions. It is understood that as the applied electric field increases, the increasing electric field tends to displace, stretch, and/or breaks the bonds of the ion such that the stronger the field, the greater the induced dipole, quadripole, or higher order moments of the ion. These, in turn, affect the relative mobility of the specific ion. The result of relating these aspects is to define a unique mobility signature for the ion species of interest. This also turns out to be device-independent.
• V C (E) dafact ., . l+ ⁇ ⁇ > + ⁇ — E s (t) > (i) ah.
• Vc-compensation voltage peak position
• ⁇ s-electric field strength ⁇ s-electric field strength
• f(t)- waveform parameters waveshape and so forth
• Equation 6 An expression for the compensation field required to enable an ion to pass through the gap can be obtained by substituting Equations 2, 3, and 4 into Equation 5 as shown in Equation 6:
• this compensation electric field can be predicted precisely when the alpha parameter for the ion species, the waveform f(i) , and the amplitude of the asymmetric waveform E max are known.
• the criteria for choosing the level of approximation of alpha is first to ensure that the method of extracting the alpha parameter uses the least number of individual parameters of the experimental device. Second, the result should contain the fewest number of adjustable parameters, and the approximation curves should be within the experimental error bars. In the next section, the general method to extract the alpha parameter is described and then applied in the subsequent section.
• Equation 7 The function of ⁇ (E) can be given as a polynomial expansion into a series of electric field strength E degrees as shown in Equation 7:
• Equation 7 Substituting Equation 7 into Equation 6 provides a value of the compensation voltage as shown in Equation 8 where an uneven polynomial function is divided by an even polynomial function. Therefore an odd degree polynomial is placed after the identity sign to approximate experimental results:
• Equation 9 This allows the a comparison of the expected coefficient (approximated) to be compared to the values of alpha parameter as shown in Equation 9:
• alpha parameters can be calculated by inverting the formula by using an approximation of the experimental results per Equation 10:
• any number of polynomial terms can be determined from Equation 10 though a practical limit exists as the number of polynomial terms in the experimental result of the approximation c 2n+1 should be higher than the expected number of alpha coefficients 2n . Since the size of n depends on the experimental error, the power of the approximation of the experimental curves C(E S ) cannot be increased without limit. Usually N experimental points of Cj(E s i) exist for the same ion species and experimental data can be approximated by the polynomial using a conventional least-square method. Finally, the number series terms cannot exceed the number of experimental points so increasing the number of series terms above the point where the fitted curves are located within the experimental error bars in unreasonable.
• nine data points were identified for each of the eight ketones of Fig. 8, based on the data collected in Table 1 of Fig. 8C. These can be used to compute the a curve for that species, such as with a piecewise linear approximation to the curve.
• two data points for butanone are a(Vcomp-a, Vrf-a) and b(Vcomp-b, Vrf-b). Between these two points, the slope and sign of the butanone curve can be computed. More complete characterization of the curve, such as with polynomial curve fitting, is also possible.
• this data set becomes part of a data store for use in identification of the species of an unknown detected ion species for which two data points are collected and the corresponding curve data is computed.
• Figs. 9 A and 9B thus express the function for individual ketones spanning electric fields of 0 to 80 Td (-23 kV/cm), expressed as a percentage change in alpha as a function of field conditions.
• These plots are fundamental signature features of these ion species that are independent of the drift tube parameters and can be used in other mobility spectrometers.
• the function can be favorably used in practice of the invention to provide a mobility identification data set that is device-independent.
• ion species are identified based on ion mobility dependence of the species under various field conditions.
• characteristic changes in ion mobility based on changes in field strength and field compensation, are recorded and stored for a library of known compounds;
• data is collected for the sample under test for a variety of field conditions;
• a comparison of detection data for the sample under test versus the stored data enables identification of the compounds in the sample.
• the quality of stored data and strength of the mobility relationship enables improved species identification.
• the invention is applicable not only to planar field asymmetric ion mobility systems but may be applied in general to ion mobility spectrometry devices of various types, including various geometries, ionization arrangements, detector arrangements, and the like, and brings new uses and improved results even as to structures which are all well known in the art.
• the present invention is not limited to planar configurations of the examples and may be practiced in any other configurations, including radial and cylindrical FALMS devices.
• the output of the FALMS filter may be detected off board of the apparatus, such as in a mass spectrometer or other detector, and still remains within the spirit and scope of the present invention.
• This discussion has been focused on detection and identification of species of ions.
• this invention is broader and can be applied to any system for identification of unknown species of ions traveling through a varying controlled excitation field, the identification being based on the known characteristic travel behavior of the species under the varying field conditions.
• the ion or ions to be identified may be traveling alone or in a group of ions of same or differing characteristic travel behavior.
• the field may be compensated in any of various manners as long as a species of interest is returned to the center of the flow and permitted to pass through the filter while all other species are retarded or neutralized.
• Identification is made based on known field-dependent differential mobility behavior of at least one species of ions traveling in the field at known field conditions.
• Figs. 10A-10F A Process for Identification of Compounds Focusing attention now on Figs. 10A-10F a specific sequence of steps will be described that may be carried out to perform species identification in several of the embodiments of the present invention, which are provided by way of illustration and not limitation.
• the sequence of steps would be performed by the microprocessor 46 which is associated with the ion mobility spectrometer device 10.
• the microprocessor 46 provides digital control signals to the RF dispersion voltage generator 42 and compensation voltage generator 44 to control the desire drive voltages for the filter 24. These may also include for example, digital to analog converters that are not shown in detail in the drawings here.
• the microprocessor 46 coordinates the application of specific RF dispersion voltages Vrf and compensation voltages Vcomp also taking into account the function of observing responses from the detector 26 as read through the analog to digital converter 48. By detecting attributes (such as the peaks) of observed abundances of a particular ion species across a range of Vrf voltages, the microprocessor 46 can thus take steps to identify particular compounds. These may include, for example, comparing or correlating particular "response curve" data against a library of response curve data as stored in the memory 47. They can also include computation of curve parameters. The results of the comparison operation can be provided in the form of an appropriate output device such as a display or personal computer or the like, or maybe provided by electrical signals through an interface to other data processing equipment.
• a state 1000 is entered into the microprocessor 46 in which a compound is to be analyzed.
• the compound is known and identified, such as by a user supplying an identifying text string to the computer.
• a sequence of steps is then performed by which data is to be acquired concerning the known chemical compound.
• a next state 1002 is thus entered in which a range of dispersion voltages Vrf and compensation voltages Vcomp are determined by the processor 46.
• These ranges include a beginning voltage (b) and an end voltage (s) and step voltage(s) to be applied to each of the ranges Vrf is thus varied from an initial value Vrf(b) to a final value Vrf(e) by a step amount Vrf(s).
• Vcomp is to be varied from Vcomp(b) to a final value Vcomp(e) by a step amount Vcomp(s).
• step 1004 is entered in which the Vrf is allowed to step through a range of values.
• step 1008 is entered next in which the compensation voltage Vcomp is also swept or stepped through a series of values or ranges.
• processing returns to state 1008 in which the next compensation voltage is applied.
• processing proceeds to a state 1014 wherein a test is made to see if all of the dispersion have been applied.
• a state 1018 to identify features of interest.
• it will be the peak locations that are of interest.
• a response value for a specific Vcomp is determined and its corresponding amplitude, a, is detected and stored.
• the response curve data, or certain attributes thereof such as the peak locations are then stored as a data object P (or table) as shown in Fig. 10B.
• Such an object will typically contain an identification of the tested compound such a text string.
• a set of the applied dispersion voltages Vrf are also stored of course.
• a corresponding peak compensation voltage is stored for each such dispersion voltage Vrf . Specifically, what is stored is at least the compensation voltage Vcomp at which a peak was observed, and typically the corresponding amplitude of the response (abundance) observed at that peak.
• An example data element of object P is thus shown where for a single RF dispersion voltage, Vrf-1, peaks were observed at compensation voltages Vcl 1, ..., Vein having corresponding amplitudes al 1, ..., aln.
• Vrf-1 a single RF dispersion voltage
• a state 1220 is entered in which features such as peaks of the response are identified for each peak a corresponding compensation voltage and amplitude may be identified and these stored to a candidate measurement vector P'.
• the candidate vector P' thus represents a series of data that need to be tested against a number of candidate compounds.
• the candidate vector P' is then analyzed in states 1230 and/or 1240 by looking up corresponding counterparts in the library of reference vector objects P, and scoring a match between P and P' . These steps may be iterated until such time as a match or a best match is determined in a state 1250.
• any number of techniques may be used to determine a degree of match between P and P'. For example, if the elements (Vcomp, a) of P and P' are considered to be data points in Euclidian geometry space, a distance can be computed. The comparison with the smallest Euclidian distance can then be selected as the best match.
• other recognition techniques may be used or to determine an identify of an unknown compound, for example, are there more sophisticated signal processing techniques such as correlation may be used to resolve peaks; or other known pattern recognition algorithms, neural networks or artificial intelligence techniques may be used to find a best match for P'.
• Fig. 10D shows a series of steps that may be added to the data acquisition phase and the chemical recognition phase to take advantage of second order data processing characteristics.
• a series of states 1020, 1022, 1024 and 1026 may be added which attempt to curve-fit specific attributes of the measured response.
• a state 1020 may be entered in which for each data element of the object P a vector, z, is'formed consisting of the peak compensation voltages vei l, vcl2,...vclm.
• This vector is in fact a vector of point locations for the peaks observed for a range of compensation voltages.
• this may correspond to for example locating the points 601-1,...601-m,...601-n corresponding to peak height and locations for the monomer ions of interest.
• a curve may then be fit through these peaks such as by applying a curve fitting algorithm, in state 1024.
• the ⁇ and ⁇ coefficients can then be stored in the state 1026 associated with the vector. The chemical is thus identified by a curve fit to its peak locations approximating its mobility ( coefficient) behavior.
• a corresponding set of steps 1270, 1272 and 1274 would be typically added to the chemical recognition process.
• peaks would be identified instead of comparing raw data values in states 1270 and 1272 by performing a curve fit to observe data and then determining ⁇ and ⁇ coefficients.
• state 1274 the ⁇ and coefficients would be tested to determine closest matches in the P object library.
• Fig. 10F shows a series of steps that may be used to identify or distinguish peaks in the acquisition phase.
• initial data may be added to the objects P by identifying peaks as a cluster peak or monomer peak. Specifically, if a peak shift is observed as a range as a range of field condition voltages (e.g., Fog.
• Fig. 10G shows additional processing steps that might be performed in the chemical recognition state to take advantage of the situation of Figure 8 A and 8B in which monomer and cluster ion behavior is observed. Specifically, these steps in Figure 10G might be added as further steps 1280 in the recognition phase. Here for every candidate peak P' corresponding monomer peak in the reference array P is compared. A score is then associated with the closest of the match in state 1284 similarly in state 1286 a cluster peak may be compared with its corresponding in the peak library P. A score sc is then determined in step 1288 depending on the closest of this match.
• a final score sf can be associated with weighting the monomer peak score and the cluster peak score by weighting factors wm and wc for example in an instance where cluster peaks are expected to provide more information than monomer peaks, cluster peaks might be weighted highly and monomer peaks relatively low or zero factor.
• This weighting is understood now how both monomer and cluster peak identification can be combined to further refine compound identification. It will be evident to one skilled in the art that various modifications and variations may be made to the present invention without departing from the spirit and scope herein. For example, although illustrated in Fig. 2 was a single filter 24 and detector 28, it should be understood that a series of filters 24 can be applied to a specific gas ionized sample S. The first can be used as a pre-filter to limit chemical species to a particular range of species that are know to be of interest, with the second filter in the series being used to provide for detailed sweeping at precise incrementing voltages to provide for greater resolution.

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